Аrtificial intelligence tools for managing the behavior of economic agents in marketing activities
Abstract
The relevance of the use of artificial intelligence tools for managing the behavior of economic agents in marketing activities is substantiated. The subject of research in the article is artificial intelligence tools for managing the behavior of economic agents in marketing activities. The goal of the article is to study the possibilities of artificial intelligence tools for managing the behavior of economic agents in marketing activities. Objective: to identify the object and subject of management when using marketing tools of artificial intelligence, schematically display their relationships and group similar tools, for further description of their capabilities, advantages and disadvantages with the aim of using them in the marketing activities of enterprises. General scientific methods are used: system analysis - to determine the features of artificial intelligence tools for managing the behavior of economic agents in marketing activities, structural (functional) analysis - to identify the main functions of artificial intelligence tools for managing the behavior of economic agents in marketing activities. The results were obtained: the grouped artificial intelligence tools for managing the behavior of economic agents in marketing activities are presented, and the interaction schemes of objects and management subjects of each group of tools are presented. Conclusions: the use of artificial intelligence tools to manage the behavior of economic agents in marketing activities will allow enterprises to get more profit due to an increase in the number of goods sold, and customers to spend money on meeting relevant needs.
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Bean R. How Big Data and AI Are Driving Business Innovation in 2018. MIT Sloan. Management Review. 2018.
Miller S. AI: Augmentation, more so than automation. Asian Management Insights. 2018. № 5(1). pp. 1-20.
Daugherty, P. R., & Wilson, H. J. Human+ Machine: Reimagining Work in the Age of AI: Harvard Business Press. 2018.
Agrawal, A., Gans, J., & Goldfarb, A. Prediction Machines: The simple economics of artificial intelligence: Harvard Business Press. 2018.
Panetta, K. Gartner Top 10 Strategic Technology Trends for 2018. URL: https://www.gartner.com/smarterwithgartner/gartner-top-10-strategic-technologytrends-for-2018/
Phillips-Wren G., Jain L. Artificial intelligence for decision making. International Conference on Knowledge-Based and Intelligent Information and Engineering Systems. Springer, Berlin, Heidelberg. 2006. pp. 531-536.
Jarrahi M. H. Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making. Business horizons. 2018. №. 4. pp. 577-586.
Fast N. J., Schroeder J. Power and decision making: new directions for research in the age of artificial intelligence. Current opinion in psychology. 2020. Т. 33. pp. 172-176.
Raisch S., Krakowski S. Artificial intelligence and management: The automation–augmentation paradox. Academy of Management Review. 2021. №. 1. pp. 192-210.
Principles of Marketing, 2nd European Edition / Ph. Kotler et al. New Jersey: Prentice Hall, 1999. 1032 p.
AI Marketing Tools: 21 Online Tools You Can Try Today / Venture harbour. URL: https://www.ventureharbour.com/online-marketing-ai-machine-learning-tools-you-can-try-today/
Top 20 AI Marketing Tools to Grow Your Business in 2022 / Influencer marketin ghub. URL: https://influencermarketinghub.com/ai-marketing-tools/
Bean, R. (2018). How Big Data and AI Are Driving Business Innovation in 2018. MIT Sloan. Management Review.
Miller, S. (2018). AI: Augmentation, more so than automation. Asian Management Insights, 5(1), 1-20.
Daugherty, P. R., & Wilson, H. J. (2018). Human+ Machine: Reimagining Work in the Age of AI: Harvard Business Press.
Agrawal, A., Gans, J., & Goldfarb, A. (2018). Prediction Machines: The simple economics of artificial intelligence: Harvard Business Press.
Panetta, K. (2018). Gartner Top 10 Strategic Technology Trends for 2018. Retrieved from: https://www.gartner.com/smarterwithgartner/gartner-top-10-strategic-technologytrends-for-2018/
Phillips-Wren G., Jain L. (2006) Artificial intelligence for decision making. International Conference on Knowledge-Based and Intelligent Information and Engineering Systems. Springer, Berlin, Heidelberg.
Jarrahi M. H. (2018) Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making. Business horizons, 4, 577-586.
Fast N. J., Schroeder J. (2020) Power and decision making: new directions for research in the age of artificial intelligence. Current opinion in psychology, 33, 172-176.
Raisch S., Krakowski S. (2021) Artificial intelligence and management: The automation–augmentation paradox. Academy of Management Review, 1, 192-210.
Kotler Ph. (Ed.). (1999) Principles of Marketing, 2nd European Edition. New Jersey: Prentice Hall.
AI Marketing Tools: 21 Online Tools You Can Try Today / Venture harbour. Retrieved from: https://www.ventureharbour.com/online-marketing-ai-machine-learning-tools-you-can-try-today/
Top 20 AI Marketing Tools to Grow Your Business in 2022 / Influencer marketin ghub. Retrieved from: https://influencermarketinghub.com/ai-marketing-tools/
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